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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Mathematical Modeling of the Origins of Life

The emergence of early metabolism - a network of catalyzed chemical reactions that supported self-maintenance, growth, reproduction and evolution of the ancestors of contemporary cells (protocells) was a critical, but still very poorly understood step on the path from inanimate to animate matter. Here, it is proposed and tested through mathematical modeling of biochemically plausible systems that the emergence of metabolism and its initial evolution towards higher complexity preceded the emergence of a genome. Even though the formation of protocellular metabolism was driven by non-genomic, highly stochastic processes the outcome was largely deterministic, strongly constrained by laws of chemistry. It is shown that such concepts as speciation and fitness to the environment, developed in the context of genomic evolution, also held in the absence of a genome.

Pohorille, Andrew↗
DOE OSTI2018

Mathematical modeling of within-host Zika virus dynamics

Recent Zika virus outbreaks have been associated with severe outcomes, especially during pregnancy. A great deal of effort has been put toward understanding this virus, particularly the immune mechanisms responsible for rapid viral control in the majority of infections. Identifying and understanding the key mechanisms of immune control will provide the foundation for the development of effective vaccines and antiviral therapy. In this paper, we outline a mathematical modeling approach for analyzing the within-host dynamics of Zika virus, and we describe how these models can be used to understand key aspects of the viral life cycle and to predict antiviral efficacy.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Mathematical Modeling of Electrochemical Flow Capacitors

Electrochemical flow capacitors (EFCs) for grid-scale energy storage are a new technology that is beginning to receive interest. Prediction of the expected performance of such systems is important as modeling can be a useful avenue in the search for design improvements. Models based off of circuit analogues exist to predict EFC performance, but these suffer from deficiencies (e.g. a multitude of fitting constants that are required and the ability to analyze only one spatial direction at a time). In this paper mathematical models based off of three-dimensional macroscopic balances (similar to models for porous electrodes) are reported. Unlike existing three-dimensional porous electrode-based approaches for modeling slurry electrodes, advection (i.e., transport associated with bulk fluid motion) of the overpotential is included in order to account for the surface charge at the interface between flowing particles and the electrolyte. Doing so leads to the presence of overpotential boundary layers that control the performance of EFCs. These models were used to predict the charging behavior of an EFC under both flowing and non-flowing conditions. Agreement with experimental data was good, including proper prediction of the steady-state current that is achieved during charging of a flowing EFC. (C) The Author(s) 2015. Published by ECS. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives 4.0 License (CC BY-NC-ND, http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is not changed in any way and is properly cited. For permission for commercial reuse, please email: oa@electrochem.org. All rights reserved.

Hoyt, NC↗
NASA NTRS1979

Mathematic modeling of the Earth's surface and the process of remote sensing

It is shown that real data from remote sensing of the Earth from outer space are not best suited to the search for optimal procedures with which to process such data. To work out the procedures, it was proposed that data synthesized with the help of mathematical modeling be used. A criterion for simularity to reality was formulated. The basic principles for constructing methods for modeling the data from remote sensing are recommended. A concrete method is formulated for modeling a complete cycle of radiation transformations in remote sensing. A computer program is described which realizes the proposed method. Some results from calculations are presented which show that the method satisfies the requirements imposed on it.

Balter, B. M.↗
DOE OSTI2020

Mathematical Modeling of Liquid-Phase Alkylation of Benzene with Ethylene Considering the Process Unsteadiness

Ethylbenzene is a key intermediate in the manufacture of styrene that is an important industrial monomer. Ethylbenzene is produced by benzene alkylation using either gas-phase or liquid-phase methods. The liquid-phase alkylation that uses liquid acidic catalysts needs to be improved. We develop a mathematical model for the liquid-phase benzene alkylation. The reaction scheme, designed with a due analysis of desired and side reactions, and with the analysis of the formation of deactivating agents, reflects, in particular, the influence of the concentration of heavy hydrocarbons on the catalyst activity. The account of the catalyst deactivation by heavy alkylaromatics allows predictions of the temporal changes in the outputs of the alkylation process. In particular, the decrease of the ethylbenzene concentration by 2–3 wt % and increase of the polyalkylate outlet concentration by 1.5–2 wt % are the results of the catalyst deactivation. These effects, however, can be compensated by 1.3-time increase of polyalkylate supply and by the temperature increase up to 398 K. Finally, the calculations also show that it is possible to decrease the supply of fresh catalyst from 0.498 to 0.472 t/hour without loss in the yield of ethylbenzene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Mathematical modelling the pathway of genomic instability in lung cancer

Genomic instability plays a significant role in lung cancer. Although substantial research has been conducted using both clinical and theoretical studies, it is still a hotly debated issue to whether genomic instability is necessary or whether genomic instability precedes oncogenes activation and tumor suppressor genes inactivation for lung cancer. In response to this issue, we come up with a mathematical model incorporating effects of genomic instability to investigate the genomic instability pathway of human lung cancer. The presented model are applied to match the incidence rate data of lung cancer from the Life Span Study cohort of the atomic bomb survivors in Nagasaki and Hiroshima and the Surveillance Epidemiology and End Results registry in the United States. Model results suggest that genomic instability is necessary in the tumorigenesis of lung cancer, and genomic instability has no significant impact on the net proliferation rate of cells by statistical criteria. By comparing the results of the LSS data to those of the SEER data, we conclude that the genomic instability pathway exhibits a sensitivity to radiation exposure, more intensive in male patients.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1992

Mathematical modeling of bent-axis hydraulic piston motors

Each of the DSN 70-m antennas uses 16 bent-axis hydraulic piston motors as part of the antenna drive system. On each of the two antenna axes, four motors are used to drive the antenna and four motors provide counter torque to remove the backlash in the antenna drive train. This article presents a mathematical model for bent-axis hydraulic piston motors. The model was developed to understand the influence of the hydraulic motors on the performance of the DSN 70-m antennas' servo control system.

Bartos, R. D.↗
DOE OSTI2021

Mathematical model of a personalized neoantigen cancer vaccine and the human immune system

Cancer vaccines are an important component of the cancer immunotherapy toolkit enhancing immune response to malignant cells by activating CD4 + and CD8 + T cells. Multiple successful clinical applications of cancer vaccines have shown good safety and efficacy. Despite the notable progress, significant challenges remain in obtaining consistent immune responses across heterogeneous patient populations, as well as various cancers. We present a mechanistic mathematical model describing key interactions of a personalized neoantigen cancer vaccine with an individual patient’s immune system. Specifically, the model considers the vaccine concentration of tumor-specific antigen peptides and adjuvant, the patient’s major histocompatibility complexes I and II copy numbers, tumor size, T cells, and antigen presenting cells. We parametrized the model using patient-specific data from a clinical study in which individualized cancer vaccines were used to treat six melanoma patients. Model simulations predicted both immune responses, represented by T cell counts, to the vaccine as well as clinical outcome (determined as change of tumor size). This model, although complex, can be used to describe, simulate, and predict the behavior of the human immune system to a personalized cancer vaccine.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Mathematical Model for Li-S Cell with Shuttling-Induced Capacity Loss Approximation

Lithium sulfur (Li-S) batteries have the potential to outperform the current lithium ion batteries and transform the technology of the future. However, dissolution, diffusion, and shuttling of the dissolved polysulfides result in parasitic reactions and substantial capacity loss. To provide a better understanding of the shuttling process, a 1D porous electrode mathematical model has been developed in this paper. An approximation method is used to account for the shuttling-induced capacity loss by adding an extra source/sink term in the material balance equations for the species involved in the parasitic reactions. Shuttling constants used in the source terms can be determined by fitting the model predictions to the experimental measurements. Here, the results showed that by including the approximation method, the model was able to predict the active material loss and the continuous decrease of volume fractions of Li 2 S on the cathode surface. The model sheds light on the capacity loss mechanism occurring inside the cell as a result of the shuttling of polysulfides.

25 ENERGY STORAGE↗
NASA NTRS1987

Mathematical modeling of a photovoltaic-laser energy converter for iodine laser radiation

Space-based laser power systems will require converters to change laser radiation into electricity. Vertical junction photovoltaic converters are promising devices for this use. A promising laser for the laser power station is the t-C4F9I laser which emits radiation at a wavelength of 1.315 microns. This paper describes the results of mathematical modeling of a photovoltaic-laser energy converter for use with this laser. The material for this photovoltaic converter is Ga(53)In(47)As which has a bandgap energy of 0.94 eV, slightly below the energy of the laser photons (0.943 eV). Results of a study optimizing the converter parameters are presented. Calculated efficiency for a 1000 vertical junction converter is 42.5 percent at a power density of 1 x 10 to the 3d power w/sq cm.

Walker, Gilbert H.↗
DOE OSTI2013

Empirical and physics based mathematical models of uranium hydride decomposition kinetics with quantified uncertainties.

Metal particle beds have recently become a major technique for hydrogen storage. In order to extract hydrogen from such beds, it is crucial to understand the decomposition kinetics of the metal hydride. We are interested in obtaining a a better understanding of the uranium hydride (UH3) decomposition kinetics. We first developed an empirical model by fitting data compiled from different experimental studies in the literature and quantified the uncertainty resulting from the scattered data. We found that the decomposition time range predicted by the obtained kinetics was in a good agreement with published experimental results. Secondly, we developed a physics based mathematical model to simulate the rate of hydrogen diffusion in a hydride particle during the decomposition. We used this model to simulate the decomposition of the particles for temperatures ranging from 300K to 1000K while propagating parametric uncertainty and evaluated the kinetics from the results. We compared the kinetics parameters derived from the empirical and physics based models and found that the uncertainty in the kinetics predicted by the physics based model covers the scattered experimental data. Finally, we used the physics-based kinetics parameters to simulate the effects of boundary resistances and powder morphological changes during decomposition in a continuum level model. We found that the species change within the bed occurring during the decomposition accelerates the hydrogen flow by increasing the bed permeability, while the pressure buildup and the thermal barrier forming at the wall significantly impede the hydrogen extraction.

08 HYDROGEN↗
DOE OSTI2020

Mathematical model of broadly reactive plasma cell production

Strain-specific plasma cells are capable of producing neutralizing antibodies that are essential for clearance of challenging pathogens. These neutralizing antibodies also function as a main defense against disease establishment in a host. However, when a rapidly mutating pathogen infects a host, successful control of the invasion requires shifting the production of plasma cells from strain-specific to broadly reactive. In this study, we develop a mathematical model of germinal center dynamics and use it to predict the events that lead to improved breadth of the plasma cell response. We examine scenarios that lead to germinal centers that are composed of B-cells that come from a single strain-specific clone, a single broadly reactive clone or both clones. We find that the initial B-cell clonal composition, T-follicular helper cell signaling, increased rounds of productive somatic hypermutation, and B-cell selection strength are among the mechanisms differentiating between strain-specific and broadly reactive plasma cell production during infections. Understanding the contribution of these factors to emergence of breadth may assist in boosting broadly reactive plasma cells production.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1985

Mathematical Models of Continuous Flow Electrophoresis

Development of high resolution continuous flow electrophoresis devices ultimately requires comprehensive understanding of the ways various phenomena and processes facilitate or hinder separation. A comprehensive model of the actual three dimensional flow, temperature and electric fields was developed to provide guidance in the design of electrophoresis chambers for specific tasks and means of interpreting test data on a given chamber. Part of the process of model development includes experimental and theoretical studies of hydrodynamic stability. This is necessary to understand the origin of mixing flows observed with wide gap gravitational effects. To insure that the model accurately reflects the flow field and particle motion requires extensive experimental work. Another part of the investigation is concerned with the behavior of concentrated sample suspensions with regard to sample stream stability particle-particle interactions which might affect separation in an electric field, especially at high field strengths. Mathematical models will be developed and tested to establish the roles of the various interactions.

Saville, D. A.↗
NASA NTRS1999

Friction-Stir Welding and Mathematical Modeling

The friction-stir welding process is a remarkable way for making butt and lap joints in aluminum alloys. This process operates by passing a rotating tool between two closely butted plates. Through this process it generates a lot of heat and heated material is stirred from both sides of the plates in which the outcome will one high quality weld. My research has been done to study the FSW through mathematical modeling, and using modeling to better understand what take place during the friction-stir weld.

Rostant, Victor D.↗
NASA NTRS1986

Evaluation of a nonlinear parameter extraction mathematical model including the term C(subm(sub delta e squared))

Shuttle flight test data were used to determine values for the short-period parameters. The best identified, as judged by its estimated standard deviation, was the elevon effectiveness parameter C (sub m (sub sigma e squared)). However, the scatter about the preflight prediction of C (sub m (sub sigma e squared)) was large. Other investigators have suggested that adding nonlinear terms to the mathematical model used to identify C (sub m (sub sigma e)) could reduce the scatter. The results of this investigation show that C (sub m (sub sigma e squared)) is the only identifiable nonlinear parameter applicable and that the changes in C (sub m (sub sigma e)) values when C (sub m (sub sigma e squared)) is included are in the order of ten percent for the data estimated.

Suit, W. T.↗
NASA NTRS1987

Meteor velocity distribution and an optimum monitoring mathematical model

At present, there are a great number of radio meteor, ionosphere and rocket observation data for the altitude range of 80 to 100 km which indicate the existence of large scale circulation systems in the mesopause to low thermosphere range which change regularly with season and latitude. But the existing observation network and observation programs are not optimal for revealing the main factors forming the circulation mode at these altitudes. A generalized optimum monitoring mathematical model is offered for consideration. The model input data are distribution density, response function, individual measurement root mean square uncertainty and detection effectiveness function. The model makes it possible to obtain the observation distribution density, the minimal possible dispersion and optimized system effectiveness.

Volkov, N. G.↗
DOE OSTI2015

TU-CD-304-05: 4Ï€ Non-Coplanar Radiotherapy: From Mathematical Modeling to Clinical Implementation

Purpose: To develop and clinically implement 4π radiotherapy, an inverse optimization platform that maximally utilizes non-coplanar intensity modulated radiotherapy (IMRT) beams to significantly improve critical organ sparing. Methods: A 3D scanner was used to digitize the human and phantom subject surfaces, which were positioned in the computer assisted design (CAD) model of a TrueBeam machine to create a virtual geometrical model, based on which, the feasible beam space was calculated for different tumor locations. Beamlets were computed for all feasible beams using convolution/superposition. A column generation algorithm was employed to optimize patient specific beam orientations and fluence maps. Optimal routing through all selected beams were calculated by a level set method. The resultant plans were converted to XML files and delivered to phantoms in the TrueBeam developer mode. Finally, 4π plans were recomputed in Eclipse and manually delivered to recurrent GBM patients. Results: Compared to IMRT utilizing manually selected beams and volumetric modulated arc therapy plans, markedly improved dosimetry was observed using 4π for the brain, head and neck, liver, lung, and prostate patients. The improvements were due to significantly improved conformality and reduced high dose spillage to organs mediolateral to the PTV. The virtual geometrical model was experimentally validated. Safety margins with 99.9% confidence in collision avoidance were included to the model based model accuracy estimates determined via 300 physical machine to phantom distance measurements. Automated delivery in the developer mode was completed in 10 minutes and collision free. Manual 4 π treatment on the GBM cases resulted in significant brainstem sparing and took 35–45 minutes including multiple images, which showed submillimeter cranial intrafractional motion. Conclusion: The mathematical modeling utilized in 4π is accurate to create and guide highly complex non-coplanar IMRT treatments that consistently and significantly outperform human-operator-created plans. Deliverability of such plans is clinically demonstrated. This work is funded by Varian Medical Systems and the NSF Graduate Research Fellowship DGE-1144087.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1999

Mathematical model to estimate risk of calcium-containing renal stones

BACKGROUND/AIMS: Astronauts exposed to microgravity during the course of spaceflight undergo physiologic changes that alter the urinary environment so as to increase the risk of renal stone formation. This study was undertaken to identify a simple method with which to evaluate the potential risk of renal stone development during spaceflight. METHOD: We used a large database of urinary risk factors obtained from 323 astronauts before and after spaceflight to generate a mathematical model with which to predict the urinary supersaturation of calcium stone forming salts. RESULT: This model, which involves the fewest possible analytical variables (urinary calcium, citrate, oxalate, phosphorus, and total volume), reliably and accurately predicted the urinary supersaturation of the calcium stone forming salts when compared to results obtained from a group of 6 astronauts who collected urine during flight. CONCLUSIONS: The use of this model will simplify both routine medical monitoring during spaceflight as well as the evaluation of countermeasures designed to minimize renal stone development. This model also can be used for Earth-based applications in which access to analytical resources is limited.

NASA Center JSC↗